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Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
TqSdk
86 documents
Quantpedia
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Binance API docs
45 documents
Quantopian lectures
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

20,364 documents

Quant Q&A

The document asks how quantitative strategies can compare derivatives with different expiries, prices, and volatility characteristics, using commodity futures as an example. It highlights a limitation of applying a single-price time-series method, such as a…

FuturesCommoditiesDerivatives pricingTechnical indicators
Quant Q&A

The document distinguishes adapted and predictable processes using a Brownian motion and its natural filtration. It compares the Brownian path itself, a version delayed by one time unit, and a version shifted forward by one time unit. The first is adapted;…

Statistics
Quant Q&A

The document surveys strategies in which receiving market data or reaching an exchange sooner may affect execution. It describes latency arbitrage as a contest over speed, with examples including arbitrage across fragmented equity venues, triangular…

High-frequency tradingArbitrageMarket makingExecution
Quant Q&A

The document works through a hedge for a company planning to issue 180-day commercial paper. Because the company benefits from higher short-term rates when issuing the paper, it can short Eurodollar futures; the example scales the position by comparing the…

FuturesFixed incomeRisk managementPosition sizing
Quant Q&A

The document explains why a less liquid corporate bond will often have a wider bid–ask spread than a comparable, easier-to-source bond. Investors may require compensation for the risk of holding an asset that could be difficult to sell, while the bond’s…

Fixed incomeMarket microstructure
Quant Q&A

The document considers a European payoff equal to the difference between the highest and lowest observed stock prices over a discrete period. Under its stated multi-step binomial model, the stock is assumed to be a martingale and the risk-free bond has…

OptionsDerivatives pricingStatistics
Quant Q&A

The document offers a qualitative guide to who commonly trades interest rate swaps and related US Treasury instruments at different points on the curve. It associates short-dated swaps with macro traders, hedge funds, corporates hedging loans, and banks…

Fixed incomeMarket microstructureUS markets
Quant Q&A

The document asks how to describe the distribution of the highest price reached by a cash-or-nothing digital call before expiration. It assumes the underlying follows geometric Brownian motion with constant volatility and uses the Black-style probability…

OptionsDerivatives pricingStatisticsVolatility
Quant Q&A

The document outlines a progression of methods for testing strategies that depend on timely execution, especially passive orders and cross-market hedging. For liquidity-taking strategies, top-of-book data may support conservative size assumptions that can…

Market microstructureExecutionBacktestingHigh-frequency trading
Quant Q&A

The document examines why annualized volatility estimated from weekly or other lower-frequency returns can exceed an estimate from daily returns. The square-root-of-time scaling rule relies on returns being identically distributed and independent; serial…

VolatilityStatisticsPortfolio constructionMulti-asset
Quant Q&A

A zero-mean GARCH model treats returns as conditionally centered at zero and estimates conditional variance from squared returns and past variance. If this assumption is used, the model can forecast volatility directly from the observed squared returns. When…

VolatilityStatistics
Quant Q&A

For European options with the same strike and expiry, put–call parity links their prices to the discounted forward price and implies consistent implied volatility when prices and market inputs are aligned. The discussion addresses why observed implied…

OptionsDerivatives pricingArbitrage
Quant Q&A

The document considers how to generate many Brownian bridge paths for multiple underlying assets in a Monte Carlo setting. The original routine advances through time steps and simulates one path at a time, which becomes slow when the number of simulations…

OptionsDerivatives pricingStatisticsExecution
Quant Q&A

The document asks how to choose stop-loss and take-profit thresholds from trade outcomes and expected profit estimates. It points to operations research and stochastic processes, and presents differing views: one answer argues that thresholds may be…

BacktestingRisk managementStatisticsMachine learning
Quant Q&A

A baker who will need wheat later can hedge the uncertain purchase price by going long futures contracts that mature when the wheat is needed. The document explains the cash flows at maturity: the futures gain is the spot price at maturity minus the initial…

FuturesCommoditiesRisk management
Quant Q&A

The document presents a proposed backward-time finite-difference scheme for solving the Black–Scholes partial differential equation. Starting from the option payoff at expiration, it uses a Taylor approximation to step the value backward in time. It…

OptionsDerivatives pricingStatistics
Quant Q&A

The note answers whether principal-only mortgage bond prices or yields rise when interest rates fall. Its conclusion is that prices rise, with two mechanisms contributing. First, the usual bond price relationship applies: lower market rates increase the…

Fixed income
Quant Q&A

The note explains daily variation margin by contrasting futures with assets such as stocks and options. When an investor buys a stock or an option, cash changes hands at the initial transaction; later price moves alter the account’s marked value. The…

FuturesOptionsMarket microstructure
Quant Q&A

The note explains why an American put’s value can exceed the amount available from exercising it immediately. The payoff is a lower bound: the holder can exercise and receive that amount, or keep the option alive. The right to choose later has value because…

OptionsDerivatives pricing
Quant Q&A

The document asks how to split a European option’s net present value into intrinsic value and time value when pricing with QuantLib-Python’s Black–Scholes example. It explains that intrinsic value can be obtained by applying the option’s payoff function to…

OptionsDerivatives pricing
Quant Q&A

The document distinguishes an option’s expected payoff from the effect of volatility on that payoff. Under risk-neutral pricing, an option value is the discounted expected payoff, so a larger expected payoff corresponds to a higher value. But raising…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks how to estimate wrong-way risk for an exotic option priced by Monte Carlo under the Heston stochastic volatility model. It describes a proposed framework in which market risk factors and credit risk factors are simulated jointly. Dependence…

OptionsVolatilityRisk managementDerivatives pricing
Quant Q&A

A Brownian motion is characterized by the distributions of its increments under a particular probability measure. The document explains that the same underlying sample space and paths can be assigned different probabilities, changing the distributions of…

Statistics
Quant Q&A

The document explains how Libor fixings work when an interest rate swap pays every six months but references a three month Libor rate. Libor is typically set in advance, shortly before the start of each accrual period, and paid in arrears. In the example,…

Fixed incomeDerivatives pricingRisk management